# OpenObserve MCP Server

> Use this tool when you need to query and analyze data from multiple OpenObserve instances efficiently. It solves problems of data fragmentation and slow query performance by enabling parallel execution, batching, and caching of logs, traces, and metrics. The tool accepts queries as input and outputs consolidated data, making it ideal for use cases that require unified monitoring and observability across distributed systems.

Canonical page: https://skillsregistry.net/skills/adarshba-openobserve-mcp  
JSON: https://api.skillsregistry.net/v1/skills/adarshba-openobserve-mcp

## Description

Enables querying logs, traces, and metrics from multiple OpenObserve instances via MCP tools, with parallel execution, batching, and caching.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/wom3gqr0p6)
- **Repository:** <https://github.com/adarshba/openobserve-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "adarshba-openobserve-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/adarshba-openobserve-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/adarshba-openobserve-mcp/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt